English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Identifying Time-Varying Neuromuscular System with a Recursive Least-Squares Algorithm: a Monte-Carlo Simulation Study

Olivari, M., Nieuwenhuizen, F., Bülthoff, H., & Pollini, L. (2014). Identifying Time-Varying Neuromuscular System with a Recursive Least-Squares Algorithm: a Monte-Carlo Simulation Study. In IEEE International Conference on Systems, Man and Cybernetics (SMC 2014) (pp. 3573-3578). Piscataway, NJ, USA: IEEE.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0027-808A-B Version Permalink: http://hdl.handle.net/21.11116/0000-0001-2CB9-E
Genre: Conference Paper

Files

show Files

Locators

show
hide
Description:
-

Creators

show
hide
 Creators:
Olivari, Mario1, 2, Author              
Nieuwenhuizen, FM1, 2, Author              
Bülthoff, HH1, 2, Author              
Pollini, L, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

Content

show
hide
Free keywords: -
 Abstract: A human-centered design of haptic aids aims at tuning the force feedback based on the effect it has on human behavior. For this goal, a better understanding of the influence of haptic aids on the pilot neuromuscular response becomes crucial. In realistic scenarios, the neuromuscular response can continuously vary depending on many factors, such as environmental factors or pilot fatigue. This paper presents a method that online estimates time-varying neuromuscular dynamics during force-related tasks. This method is based on a Recursive Least Squares (RLS) algorithm and assumes that the neuromuscular response can be approximated by a Finite Impulse Response filter. The reliability and the robustness of the method were investigated by performing a set of Monte-Carlo simulations with increasing level or remnant noise. Even with high level of remnant noise, the RLS algorithm provided accurate estimates when the neuromuscular dynamics were constant or changed slowly. With instantaneous changes, the RLS algorithm needed almost 8s to converge to a reliable estimate. These results seem to indicate that RLS algorithm is a valid tool for estimating online time-varying admittance.

Details

show
hide
Language(s):
 Dates: 2014-10
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1109/SMC.2014.6974484
BibTex Citekey: OlivariNBP2014_3
 Degree: -

Event

show
hide
Title: IEEE International Conference on Systems, Man and Cybernetics (SMC 2014)
Place of Event: San Diego, CA, USA
Start-/End Date: -

Legal Case

show

Project information

show

Source 1

show
hide
Title: IEEE International Conference on Systems, Man and Cybernetics (SMC 2014)
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 3573 - 3578 Identifier: ISBN: 978-1-4799-3840-7